Abstract.We have quantified the relationship between Aerosol Index (AI) measurements and plume height for young biomass burning plumes using coincident Ozone Monitoring Instrument (OMI) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements. This linear relationship allows the determination of high-altitude plumes wherever AI data are available, and it provides a data set for validating global fire plume heights in chemistry transport models. We find that all plumes detected from June 2006 to February 2009 with an AI value ≥9 are located at altitudes higher than 5 km. Older high-altitude plumes have lower AI values than young plumes at similar altitudes. We have examined available AI data from the OMI and TOMS instruments and find that large AI plumes occur more frequently over North America than over Australia or Russia/Northeast Asia. According to the derived relationship, during this time interval, 181 plumes, in various stages of their evolution, reached altitudes above 8 km.

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Abstract. We have quantified the relationship between Aerosol Index (AI) measurements and plume height for young biomass burning plumes using coincident OMI and CALIPSO measurements. This linear relationship allows the determination of high-altitude plumes wherever AI data are available, and it provides a data set for validating global fire plume injection heights in chemistry transport models. We find that all plumes detected from June 2006 to February 2009 with an AI value ≥9 are located at altitudes higher than 5 km. Older high-altitude plumes have lower AI values than young plumes at similar altitudes. We have examined available AI data from the OMI and TOMS instruments (1978–2009) and find that large AI plumes occur more frequently over North America than over Australia or Russia/Northeast Asia. According to the derived relationship, during this time interval, 181 plumes reached altitudes above 8 km. One hundred and thirty-two had injection heights ≥8 km but below 12 km, and 49 were lofted to 12 km or higher, including 14 plumes injected above 16 km.

A combination of multiplatform satellite observations and statistical data analysis are used to improve the correlation between estimates of PM 2.5 (particulate mass with aerodynamic diameter less that 2.5 µm) retrieved from satellite observations and groundlevel measured PM 2.5 . Accurate measurements of PM 2.5 can be used to assess the impact of air pollution levels on human health and the environment and to validate air pollution models. The area under study is California's San Joaquin Valley (SJV) that has a history of poor particulate air quality. Attempts to use simple linear regressions to estimate PM 2.5 from satellite-derived aerosol optical depth ( Particularly noteworthy is the fact that the PM 2.5 retrieved using the GAM captures many of the PM 2.5 exceedances that were not seen in the simple linear regression model. Implications: Particulate Mass (PM) in the air is a concern because of its effect on climate and human health. PM concentrations retrieved from satellite observations of aerosol optical depth can provide broad regional coverage that is not attained by surface sites. The techniques developed in this paper have resulted in greatly improved correlations between PM retrieved from satellite observations and PM from surface measurements in areas where the correlation is typically low. These improved retrievals can be used to fill in the gaps between surface sites and validate air quality models that are used for air quality forecasts and epidemiological studies.